Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
  • G01F9/00—Measuring volume flow relative to another variable, e.g. of liquid fuel for an engine
  • G01F9/001—Measuring volume flow relative to another variable, e.g. of liquid fuel for an engine with electric, electro-mechanic or electronic means
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/48—Diagnostic techniques
  • A61B6/481—Diagnostic techniques involving the use of contrast agents
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
  • A61B6/504—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of blood vessels, e.g. by angiography
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
  • A61B6/507—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for determination of haemodynamic parameters, e.g. perfusion CT
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
  • A61B8/06—Measuring blood flow
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
  • A61B8/46—Ultrasonic, sonic or infrasonic diagnostic devices with special arrangements for interfacing with the operator or the patient
  • A61B8/461—Displaying means of special interest
  • A61B8/466—Displaying means of special interest adapted to display 3D data
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
  • A61B8/48—Diagnostic techniques
  • A61B8/483—Diagnostic techniques involving the acquisition of a 3D volume of data
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
  • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
  • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
  • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
  • G01P5/00—Measuring speed of fluids, e.g. of air stream; Measuring speed of bodies relative to fluids, e.g. of ship, of aircraft
  • G01P5/001—Full-field flow measurement, e.g. determining flow velocity and direction in a whole region at the same time, flow visualisation
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
  • A61B6/48—Diagnostic techniques
  • A61B6/484—Diagnostic techniques involving phase contrast X-ray imaging

Definitions

• Echo Particle Image Velocimetry is a non-invasive ultrasonic
• Particle image velocimetry a common technique used for characterizing flow fields. Particles that may be used as flow tracers for such purposes include
• lipid DEFINITY®, Lantheus Medical Imaging, Inc.
• protein OptisonTM, GE Healthcare
• Echo-PIV has been found to be a promising approach, and the results obtained appear to be qualitatively meaningful.
• Blood flow pattern is the fingerprint of cardiac performance. Each heart disease has unique blood flow characteristics and any variation in the blood flow pattern may indicate a change in cardiac performance.
• echocardiography - is widely used to quantify cardiac dysfunction. While very useful, this information does not provide sufficient accuracy for characterizing complex three- dimensional flows, such as the flow in the right heart or in hearts with congenital defects.
• 3D three-dimensional
• an echocardiographic-based imaging modality can obtain three-dimensional blood velocity information from heart chambers and vasculature in or near real time.
• real time what is meant is that the rate of image acquisition is fast enough to capture the pace of the cardiac flow.
• the technology allows real-time quantification of complex three-dimensional flow fields inside the heart in both time and space. Illustrative examples of such use are provided.
• simultaneous, multi-plane recording at a high frequency e.g., 100 Hz and above
• simultaneous 2D velocity data in multiple planes are acquired and recombined a posteriori to reconstruct a 3D velocity field.
• a consistent 3D vector field can be generated.
• MPPIV Multi-Planar Partical Image Velocimetry
• perpendicular planes by ultrasound imaging with such advantages described above or by other imaging in association with models
• This method can estimate the out-of-plane component of the velocity and results in a divergence-free 3D velocity field.
• the incompressibility condition improves the interpolated field in terms of streamline length, thereby providing more value as an analytical tool since the resulted flow is more physically meaningful.
• One or multiple sets of perpendicular planes may be employed in such a
• Fig. 1 is a flowchart detailing a method embodiment and associated software design.
• Fig. 2 illustrates an example of 3D Echo-PIV results accomplished with the
• Figs. 3A and 3B chart RMS error for additional examples considering Hill's
• HSV Spherical Vortex
• Domenichini's DNS velocity field models respectively.
• FIG. 4 is a schematic illustrating a pulsatile heart-flow simulator for MPPIV
• Fig. 5 illustrates the shape of a Right Ventricle (RV) cast for the manufacture of a silicone rubber model for the flow simulator of Fig. 4.
• Fig. 6 illustrates a schematic of the two perpendicular stacks used for 3D reconstruction of the RV velocity field for the model of Fig. 5.
• RV Right Ventricle
• Fig. 7 charts the absolute value of divergence of the interpolated velocity field normalized by the total number of the grids inside the RV model.
• Fig. 8 charts the difference in normalized streamline length inside the RV model between the simply interpolated and divergence-free interpolated velocity fields.
• Figs. 9A and 9B illustrates streamlines of the RV model with Fig. 9A showing some streamlines in the simply-interpolated velocity field and Fig. 9B showing the streamlines originating at the same points for the divergence-free interpolated velocity field.
• Figs. 10A-10C illustrate selected iso-surfaces of the flow inside the RV model.
• Fig. 1 1 illustrates colored-coded velocity streamlines of the 3D divergence-free interpolated velocity field inside the RV model during an early filling phase of the model.
• Fig. 1 details one embodiment of the methodology 100.
• simultaneous multiple two dimensional ultrasound acquisitions are performed in real time for three-dimensional reconstruction of the flow field. These acquisitions are captured using a suitable scanner or probe at 1 10.
• two-dimensional Echo-PIV is used to capture in-plane velocity components in a slice of the domain for each of the planes. Together, such activity may be regarded as performing 2D echo-PIV.
• non-simultaneous imaging may be employed as in some of the examples below that are reliant on flow periodicity to assemble suitable image plane data.
• ultrasound-based velocimetry techniques are preferred or necessary in vivo (e.g., for cardiac blood flow interrogation)
• optical approaches may be applied in vitro as discussed.
• two or more perpendicular planes of captured data are employed for three-dimensional reconstruction of the flow field (i.e., for MPPIV).
• the velocity vectors are calculated based on optical flow techniques, which are in turn based on finding the displacement vector that maximizes the correlation between the corresponding regions of interest (ROIs) in two consecutive frames.
• the results measure the displacement and velocity vectors of the acoustically (or otherwise) illuminated micro-bubbles in all ROIs within each image.
• the three-dimensional reconstruction of the flow will be performed through the careful assembling of all of the velocity information. To achieve this goal, a process has been developed to read, sort, and assemble all the velocity data of two (or more) perpendicular slices obtained from echo images with contrast.
• Reading and assembling all of the obtained velocity data occurs at 130.
• ROI Region of Interest
• a predefined mask filters out the stationary parts of the images and detects the moving boundary of the ROI via image processing techniques well known in the art.
• an ordered three-dimensional Cartesian mesh will be generated with a velocity field that may be obtained by Kriging interpolation of the three-dimensional velocity vector field.
• Kriging is a group of geostatistical techniques that can be used to interpolate the value of a random field at an unobserved location from observations of its value at nearby locations.
• This 3D interpolation step first involves creating an ordered grid according to the PCS at 170.
• interpolation (optionally as described above) then proceeds from the assembly of 2D echo-PIV velocity data of the multiple planes.
• the interpolated velocity field does not necessarily satisfy the incompressibility condition of the flow in three-dimensional space, the field is modified accordingly.
• an irrotational velocity field having a divergence that cancels out the divergence of the interpolated velocity field will be added to it.
• 3D velocity correction performed in this manner creates a divergence-free velocity field that satisfies the incompressibility condition of the flow.
• the interpolated velocity field is projected into a divergence-free subspace.
• This projection is carried out by an appropriate pressure distribution to correct the velocity field.
• it is the gradient of the pressure distribution in the Navier-Stokes equations that significantly affects the divergence of the velocity field.
• u, v, w are the components of the velocity in a rectangular Cartesian coordinate system.
• the irrotational correction velocity field will be the gradient of the
• the final corrected velocity field, V int + V, (i.e., the 3D echo-PIV data) at 230 therefore satisfies flow incompressibility and continuity conditions.
• Fig. 2 illustrates a calculated flow vortex 300 formed from a trans-tricuspid jet during right ventricle (RV) diastole together with a multi-plane ultrasound imaging probe 310 and a suitable computer system 320 for receiving and processing probe image data, which systems may be connected for data transmission by wired or wireless means as indicated by the arrows.
• Vortex 300 is represented in 3D as a u-shaped curve by iso-surfaces of ⁇ 2 302 calculated from the velocity vector field (not shown) obtained from the subject 3D echo-PIV methodology.
• the Region of Interest (ROI) 304 is indicated by a white line defining the RV
• the vectors shown are inplane velocities 306, 306' acquired by 2D echo- PIV in two complementary perpendicular planes 308, 308' intersecting the RV axis.
• Example flow fields were sampled in two perpendicular stacks of planes (xy- and yz-stacks).
• Different image slices (otherwise, optionally, referred to as image planes) of the stacks were acquired using a single high-speed camera (Y3, IDTVision, Inc.), which can be replaced by an ultrasound matrix probe.
• a single camera was used for acquiring different slices of the stack in sequence by taking advantage of the periodicity of the flow.
• a multi-slice acquisition source e.g., a matrix array ultrasound transducer for multi-planar Echo-PIV
• 2D velocity fields can be acquired simultaneously on each slice of the stacks.
• each slice contained 32 x 32 samples, which were uniformly distributed. Slices in each stack were either 4, 8, 16, or 32 in number. In each stack, the distance between the slices was the same, which created a uniform stack. Furthermore, to mimic the uncertainty associated with experimentally-acquired velocity measurements, different levels of noise were introduced to the sampled data by starting from a field with no noise, then adding 15% and 30% Gaussian noise levels relative to the 3D field velocity scale. Therefore, for each benchmark flow field, a total of twelve sampled datasets were generated.
• n 64 3 is the resolution of the three-dimensional domain
• subscript T stands for true velocity field
• subscript i can be either the simply-interpolated or divergence- free interpolated velocity field.
• the Hill Spherical Vortex is a convenient benchmark for the purpose of flow validation.
• This vortex is an extreme member of the Norbury family of vortex rings that is used as a model in applications such as the motion of bubbles and droplets at high Reynolds number.
• the vorticity inside the HSV varies linearly with the distance from the axis of symmetry.
• the external flow is irrotational around a sphere, whereas the internal flow attributes to an axisymmetric vorticity distribution.
• the spherical symmetry of the HSV vector field challenges the subject methodology when computed in a Cartesian grid.
• Fig. 3A shows the RMS error calculated for the simply-interpolated
• divergence-free interpolated velocity fields generated according to the subject methodology in comparison with a HSV having a unit radius and velocity scale in a cube of size 1.5 x 1.5 x 1.5.
• 0%, 15%, 30% Gaussian noise was applied to 4, 8, 16, and 32 xy- and yz-slices captured at 32 x 32 resolution.
• the divergence-free interpolated velocity field showed an improvement with respect to the simply-interpolated field.
• the RMS error was not significantly reduced by applying the incompressibility constraint, mainly because the sampled velocity field was already divergence-free, thus providing an indirect validation of the interpolation procedure.
• the divergence correction adjusted the interpolated flow field more significantly towards reducing the difference in RMS error.
• the greater the level of uncertainty in the velocimetry data the greater the benefit of ensuring the incompressibility constraint.
• Fig. 3B shows the RMS error calculated for the simply-interpolated
• the MPPIV method is tested in an actual experimental setting.
• This test case provides preliminary experimental observations of the flow inside a model of the right ventricle.
• Fig. 4 is a schematic illustrating a pulsatile heart-flow simulator 400 employed for such purposes.
• the system includes an Nd:YLF green pump laser 402, a laser light sheet 404 for illumination of micro-fluorescent particles (not shown) inside a model 406 of the right ventricle (RV), a cylindrical lens 408 for converting laser beam light to the laser sheet, a box 410 filled with water containing RV model 406, resistance chambers 412 for adjusting the systemic venous and right atrial pressures in the RV model, a positive displacement pump 414 for creating pulsatile flow in the RV model; an open-to- atmosphere lung reservoir 416; and a computer system 418 for acquisition and/or processing.
• the geometry of the RV model 406 in the pumping phase is shown in Fig. 5. The geometry was generated using 3D echocardiography of a human subject.
• RV model Although flow inside the left heart has been extensively investigated, both in vitro and in vivo, very little quantitative information is available on flow patterns inside the right heart. The particular reasons for this include: (1 ) the non-symmetric, crescent shape of the RV, which is wrapped around the left ventricle (LV) and limits 2D echocardiographic flow evaluations, and (2) the highly time-dependent nature of RV flow.
• Fig. 6 illustrates the capture of planar velocity fields from two perpendicular stacks 420, 420' including a total of 12 slices 422, 422' covering the entire RV chamber.
• these were captured at 1000 frame per second (fps) with a highspeed camera per above.
• fps frame per second
• the velocity field in each slice was acquired separately and in sequence with a single camera.
• Stack 420 included 8 ry-slices 422 and stack 420' included 4 yz-slices 422' to cover the model.
• Fig. 7 shows a histogram of the divergence of the simply-interpolated velocity.
• the incompressibility correction (numerically
• Fig. 8 shows the histogram of the length difference between streamlines
• Figs. 9A and 9B show several sample streamlines to support the physical interpretation of this result. Specifically, Fig. 9A shows some streamlines 500 in the simply interpolated velocity field. Fig. 9B illustrates streamlines 500' originating at the same points for the divergence-free interpolated velocity field.
• the inlet valve i.e. the model's tricuspid valve
• the RV model was in the filling phase.
• a vortex ring was formed shortly after the inlet valve opened as shown in Fig. 1 1 A.
• Fig. 1 1 B One side of the ring then interacted with the nearby wall and gave rise to an enhanced local dissipation that altered the vortex structure as shown in Fig. 1 1 B.
• the inlet valve closed and the outlet valve i.e., the pulmonary valve
• the vortex structure took the shape of a streamline filament elongating toward the exit as shown in Fig. 1 1 C, which corresponds to a helical motion along the converging outflow tract.
• Fig. 12 shows corrected streamlines 500' in the early filling phase of the RV
• the boundary of RV model i.e., ROI 304 is shaded.
• the streamlines are colored based on velocity magnitude and illustrate the jet and the vortex around it.
• DSP Digital Signal Processor
• ASIC Application Specific Integrated Circuit
• FPGA Field Programmable Gate Array
• a general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine.
• the processor can be part of a computer system that also has a user interface port that communicates with a user interface, and which receives commands entered by a user, has at least one memory (e.g., hard drive or other comparable storage, and random access memory) that stores electronic information including a program that operates under control of the processor and with communication via the user interface port, and a video output that produces its output via any kind of video output format, e.g., VGA, DVI, HDMI, display port, or any other form.
• a memory e.g., hard drive or other comparable storage, and random access memory
• a processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such
• a software module may reside in Random Access Memory (RAM), flash memory, Read Only Memory (ROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
• An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium.
• the storage medium may be integral to the processor.
• the processor and the storage medium may reside in an ASIC.
• the ASIC may reside in a user terminal.
• the processor and the storage medium may reside as discrete components in a user terminal.
• Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.
• a storage media may be any available media that can be accessed by a computer.
• such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
• the memory storage can also be rotating magnetic hard disk drives, optical disk drives, or flash memory based storage drives or other such solid state, magnetic, or optical storage devices.
• any connection is properly termed a computer-readable medium.
• Disk and disc includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.
• Operations as described herein can be carried out on or over a website.
• the website can be operated on a server computer, or operated locally, e.g., by being downloaded to the client computer, or operated via a server farm.
• the website can be accessed over a mobile phone or a PDA, or on any other client.
• the website can use HTML code in any form, e.g., MHTML, or XML, and via any form such as cascading style sheets ("CSS”) or other.
• the operations may be carried out in any order of events which is logically possible, as well as any recited order of events.
• the computers described herein may be any kind of computer, either general purpose, or some specific purpose computer such as a workstation.
• the programs may be written in C, or Java, Brew or any other programming language.
• the programs may be resident on a storage medium, e.g., magnetic or optical, e.g. the computer hard drive, a removable disk or media such as a memory stick or SD media, or other removable medium.
• the programs may also be run over a network, for example, with a server or other machine sending signals to the local machine, which allows the local machine to carry out the operations described herein.

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